The size and the pace at which data is growing at this moment is unparalleled, so now more than ever businesses need to exploit the data. But it is not that easy to benefit from it - companies need to find a way through the techniques of data visualization and augmented analytics to put it to good use.

To understand data visualization in simple words "data visualization puts data in a context people can understand it". It all comes down to if data is executed properly or not, well executed data visualization can open the hidden doors of connections and insights that very well got have flown under the radar unnoticed. On the other hand poorly executed data visualization can create fear, misunderstanding and insecurity to use it in an organization.

In an article published in eWeek, Pete Schlampp the Vice President of Workday Analytics provided his polished knowledge on industries information about how to ensure that data is collected, shared and visualized in a way that is transparent, truthful and transformative all in a well secured way here are some points from that article.

1. Create a company-wide culture of respect for data

For data usage to be truly transformative, all stakeholders must buy into the idea that the effective and secure collection, storage, analysis and application of data is of paramount importance for everyone in the organization, not just the privileged few. Organizations must develop a data-centric culture-one in which data and good data practices is respected. This will require not only ongoing training but also investment in technology that prioritizes the enablement of data discovery and insight deliverability beyond the IT department.

2. Break down data silos to provide a single source of truth

over time, companies collect vast quantities of data, but all too often that data is siloed in a variety of different systems that often can't talk to each another. The result is data, data everywhere, but "ne'er a drop to drink." Breaking down these data silos is easier said than done, but it simply has to be done in order to make effective use of data-data that is relevant, real, current, contextual and provenance.

3. Provide access to data in real time

For data to be truly useful, it has to be current. All too often, however, a request for a report leads to information that is outdated. Typically, once a request is brought to the IT department, IT taps into the disparate data sources it believes will answer a specific question and then builds a data warehouse. By the time all of this happens, the question being asked or the data offered in response is likely old. At best, this is inefficient; at worst, with outdated or incorrect data being used to make strategic decisions, this is dangerous. Companies must look for ways to provide business users effective and efficient access to data in the applications in which they are already working.

4. Put data in the hands of decision makers

Once data has been freed from silos, it must be made available to the people who need it. That includes data scientists, of course, but it also includes any line-of-business employee who is making day-to-day (or, perhaps more accurately, minute-to-minute) decisions from the C-level to the support desk and beyond. Think of it as self-service data prep and discoverability: When all decision makers in the company can ask the right questions and get the right answers, the organization as a whole is empowered not just to innovate and compete but also to identify and get in front of potential gaps and vulnerabilities.

5. Make data visual

Making the right data available to the people who need it is an important step in the "democratization" and transformation of data, but the flip side of opening up data beyond data scientists is that many of the people who are accessing the data are not data scientists. To make data more understandable and more effectively applied, it's important to enable technology that allows users to quickly visualize report and share data. This will help users quickly and accurately detect patterns and trends-and generally make deeper meaning of data-with the ability to then share those insights with colleagues, partners and customers.

6. Tap into augmented analytics

Business leaders are looking for faster and smarter ways to uncover business insights from the growing volume and variety of data across their organizations. Augmented analytics-an approach that automates analysis using machine learning and natural-language generation-is considered "the next wave of disruption in the data and analytics market," according to Gartner. Through this approach, business users gain personalized insights into what's happening in an organization so that they can understand what actions they should take next.

7. Secure access to data

Providing more data access to more people does not mean providing all data access to all people. Rather, it means providing the right data access to the right people. Especially in a multi-tenant cloud-based environment, companies must ensure that appropriate security, privacy and compliance controls are in place, including (but certainly not limited to) role-based access management, encryption of data at rest and in transit, data segregation and physical security.